Enhance prominent spectral component of test set by using KM algorithm
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Affiliation:

1. College of Computer Science and Electronic Engineering, Hunan University, Changsha 410082, China; 2. Guangdong Power Grid Co., Ltd. Zhuhai Power Supply Bureau, Zhuhai 519000, China

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TP302

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    Abstract:

    In the field of integrated circuit testing, in order to improve the test data compression ratio and test generation, it is often necessary to do spectral analysis of the test set and test response and calculate their prominent spectral component. A method is proposed to enhance the prominent spectral component of test set by using KM (KuhnMunkras) algorithm. Based on the test set and its prominent spectral component, a bipartite graph and a weighting matrix are constructed. The problem of the enhancement of prominent spectral component is transformed into a bipartite graph matching problem, and then be solved by KM algorithm. After the order adjustment of test set according to the matching relationship, the correlation between prominent component and test set is increased, and the prominent spectral component is enhanced. In this paper, the experimental results about the test set of the ISCAS89 benchmark circuits show that the coefficient of the sorted test can increase by 19.05% on average, and the test set residue compression ratio basis on FDR (frequencydirected runlength) code can increase by 4.59% on average.

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  • Received:
  • Revised:
  • Adopted:
  • Online: July 20,2017
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